But if you wait around awhile, I promise you
import ants
import antspynet
# ANTsPy/ANTsPyNet processing for subject IXI002-Guys-0828-T1
t1_file = "IXI002-Guys-0828-T1.nii.gz"
t1 = ants.image_read(t1_file)
# Atropos six-tissue segmentation
atropos = antspynet.deep_atropos(t1, do_preprocessing=True, verbose=True)
# Kelly Kapowski cortical thickness
kk_segmentation = atropos['segmentation_image']
kk_segmentation[kk_segmentation == 4] = 3
gray_matter = atropos['probability_images'][2]
white_matter = (atropos['probability_images'][3] + atropos['probability_images'][4])
kk = ants.kelly_kapowski(s=kk_segmentation, g=gray_matter, w=white_matter,
its=45, r=0.025, m=1.5, x=0, verbose=1)
# Desikan-Killiany-Tourville labeling
dkt = antspynet.desikan_killiany_tourville_labeling(t1, do_preprocessing=True, verbose=True)
# DKT label propagation throughout the cortex
dkt_cortical_mask = ants.threshold_image(dkt, 1000, 3000, 1, 0)
dkt = dkt_cortical_mask * dkt
kk_mask = ants.threshold_image(kk, 0, 0, 0, 1)
dkt_propagated = ants.iMath(kk_mask, "PropagateLabelsThroughMask", kk_mask * dkt)
# Get average regional thickness values
kk_regional_stats = ants.label_stats(kk, dkt_propagated)
library( ANTsR )
library( ANTsRNet )
# ANTsR/ANTsRNet processing for subject IXI002-Guys-0828-T1
t1File <- "IXI002-Guys-0828-T1.nii.gz"
t1 <- antsImageRead( t1File )
# Atropos six-tissue segmentation
atropos <- deepAtropos( t1, doPreprocessing = TRUE, verbose = TRUE )
# Kelly Kapowski cortical thickness
kkSegmentation <- atropos$segmentationImage
kkSegmentation[kkSegmentation == 4] <- 3
grayMatter <- atropos$probabilityImages[[3]]
whiteMatter <- atropos$probabilityImages[[4]] + atropos$probabilityImages[[5]]
kk <- kellyKapowski( s = kkSegmentation, g = grayMatter, w = whiteMatter,
its = 45, r = 0.025, m = 1.5, x = 0, verbose = TRUE )
# Desikan-Killiany-Tourville labeling
dkt <- desikanKillianyTourvilleLabeling( t1, doPreprocessing = TRUE, verbose = TRUE )
# DKT label propagation throughout the cortex
dktCorticalMask <- thresholdImage( dkt, 1000, 3000, 1, 0 )
dkt <- dktCorticalMask * dkt
kkMask <- thresholdImage( kk, 0, 0, 0, 1 )
dktPropagated <- iMath( kkMask, "PropagateLabelsThroughMask", kkMask * dkt )
# Get average regional thickness values
kkRegionalStats <- labelStats( kk, dktPropagated )